GPR Signal Denoising and Target Extraction With the CEEMD Method

Handle URI:
http://hdl.handle.net/10754/622552
Title:
GPR Signal Denoising and Target Extraction With the CEEMD Method
Authors:
Li, Jing ( 0000-0002-7960-176X ) ; Liu, Cai; Zeng, Zhaofa; Chen, Lingna
Abstract:
In this letter, we apply a time and frequency analysis method based on the complete ensemble empirical mode decomposition (CEEMD) method in ground-penetrating radar (GPR) signal processing. It decomposes the GPR signal into a sum of oscillatory components, with guaranteed positive and smoothly varying instantaneous frequencies. The key idea of this method relies on averaging the modes obtained by empirical mode decomposition (EMD) applied to several realizations of Gaussian white noise added to the original signal. It can solve the mode-mixing problem in the EMD method and improve the resolution of ensemble EMD (EEMD) when the signal has a low signal-to-noise ratio. First, we analyze the difference between the basic theory of EMD, EEMD, and CEEMD. Then, we compare the time and frequency analysis with Hilbert-Huang transform to test the results of different methods. The synthetic and real GPR data demonstrate that CEEMD promises higher spectral-spatial resolution than the other two EMD methods in GPR signal denoising and target extraction. Its decomposition is complete, with a numerically negligible error.
KAUST Department:
Physical Sciences and Engineering (PSE) Division
Citation:
Jing Li, Cai Liu, Zhaofa Zeng, Lingna Chen (2015) GPR Signal Denoising and Target Extraction With the CEEMD Method. IEEE Geoscience and Remote Sensing Letters 12: 1615–1619. Available: http://dx.doi.org/10.1109/LGRS.2015.2415736.
Publisher:
Institute of Electrical and Electronics Engineers (IEEE)
Journal:
IEEE Geoscience and Remote Sensing Letters
Issue Date:
17-Apr-2015
DOI:
10.1109/LGRS.2015.2415736
Type:
Article
ISSN:
1545-598X; 1558-0571
Sponsors:
This work was supported in part by the National Natural Science Foundation of China under Grants 4143000131 and 41174097 and in part by the 973 Program under Grant 2013CB429805.
Appears in Collections:
Articles; Physical Sciences and Engineering (PSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorLi, Jingen
dc.contributor.authorLiu, Caien
dc.contributor.authorZeng, Zhaofaen
dc.contributor.authorChen, Lingnaen
dc.date.accessioned2017-01-02T09:55:29Z-
dc.date.available2017-01-02T09:55:29Z-
dc.date.issued2015-04-17en
dc.identifier.citationJing Li, Cai Liu, Zhaofa Zeng, Lingna Chen (2015) GPR Signal Denoising and Target Extraction With the CEEMD Method. IEEE Geoscience and Remote Sensing Letters 12: 1615–1619. Available: http://dx.doi.org/10.1109/LGRS.2015.2415736.en
dc.identifier.issn1545-598Xen
dc.identifier.issn1558-0571en
dc.identifier.doi10.1109/LGRS.2015.2415736en
dc.identifier.urihttp://hdl.handle.net/10754/622552-
dc.description.abstractIn this letter, we apply a time and frequency analysis method based on the complete ensemble empirical mode decomposition (CEEMD) method in ground-penetrating radar (GPR) signal processing. It decomposes the GPR signal into a sum of oscillatory components, with guaranteed positive and smoothly varying instantaneous frequencies. The key idea of this method relies on averaging the modes obtained by empirical mode decomposition (EMD) applied to several realizations of Gaussian white noise added to the original signal. It can solve the mode-mixing problem in the EMD method and improve the resolution of ensemble EMD (EEMD) when the signal has a low signal-to-noise ratio. First, we analyze the difference between the basic theory of EMD, EEMD, and CEEMD. Then, we compare the time and frequency analysis with Hilbert-Huang transform to test the results of different methods. The synthetic and real GPR data demonstrate that CEEMD promises higher spectral-spatial resolution than the other two EMD methods in GPR signal denoising and target extraction. Its decomposition is complete, with a numerically negligible error.en
dc.description.sponsorshipThis work was supported in part by the National Natural Science Foundation of China under Grants 4143000131 and 41174097 and in part by the 973 Program under Grant 2013CB429805.en
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.subjectComplete ensemble empirical mode decomposition (CEEMD)en
dc.subjectground-penetrating radar (GPR) signalen
dc.subjectsignal processingen
dc.subjecttime and frequency analysisen
dc.titleGPR Signal Denoising and Target Extraction With the CEEMD Methoden
dc.typeArticleen
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.identifier.journalIEEE Geoscience and Remote Sensing Lettersen
dc.contributor.institutionCollege of Geo-Exploration Science and Technology, Jilin University, Changchun, Chinaen
kaust.authorLi, Jingen
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